Understanding coupling dynamics of public transportation networks

Zheng, Zhihao; Huang, Zhiren; Zhang, Fan; Wang, Pu

doi:10.1140/epjds/s13688-018-0148-6

Cited by 28 publications

(19 citation statements)

References 49 publications

(53 reference statements)

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“…Generally, the method of gradually moving some nodes or connecting edges in the road network is adopted to calculate and compare the changes of connectivity or traffic efficiency indexes of the whole road network before and after the change of road network structure; accordingly, the nodes or connecting edges which calculation results vary greatly are defined as the vulnerable parts of the road network. Usually, the performance parameters of complex topological network are selected as the connectivity index or traffic efficiency index of the road network, such as the degree, betweenness centrality, community structure, and cluster coefficient [9][10][11][12][13][14][15][16][17]. Based on these indicators to identify the VURN, although the results can identify the vulnerable part of the network to a certain extent, there are obvious defects in the practical application of the identification results.…”

Section: Introductionmentioning

confidence: 99%

Urban Road Network Emergency: An Integrative Vulnerability Identification Method

Xiang

2021

Complexity

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The vulnerability of an urban road network is affected by many factors, such as internal road network layout, network structure strength, and external destructive events, which have great uncertainty and complexity. Thus, there is still no unified and definite vulnerability analysis scheme available to cities. This paper proposes an integrative vulnerability identification method for urban road networks, which mainly relates to the vulnerability connotation and characteristics analysis of urban road networks during emergency, and vulnerability comprehensive evaluation indices design based on urban road network connectivity, traffic efficiency and performance, and an empirical study on a vulnerability identification method of an urban road network. In the empirical case, a real road network and traffic operation data were used from Science and Technology Park of Shenzhen City, China. In the context of one certain emergency scenario, the stated preference survey method and maximum likelihood method are used to solve the road users’ random travel choice behavior parameters; subsequently, based on the traffic equilibrium distribution prediction, the traffic vulnerability identification methods of the road network in this region were verified before and after the emergency. The method presented here not only considers the impact of network topology changes on road network traffic function during emergency but also considers the impact of dynamic changes in road network traffic demand on vulnerability; therefore, it is closer to the actual distribution of urban road network traffic vulnerability.

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Section: Introductionmentioning

confidence: 99%

Urban Road Network Emergency: An Integrative Vulnerability Identification Method

Xiang

2021

Complexity

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“…The removal is usually based on topological indicators of the road network [7]. Road network topology surveys based on statistical indicators of complex networks have been a heated topic of debate in recent years [8,9,10]. These indicators are usually node-based methods [11] such as degree [12], centrality [13], community [14], clustering coefficients [15].…”

Section: Introductionmentioning

confidence: 99%

Measuring road network topology vulnerability by Ricci curvature

Gao

Xing-quan

Liu

et al. 2019

Physica A: Statistical Mechanics and its Applications

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Describing the basic properties of road network systems, such as their robustness, vulnerability, and reliability, has been a very important research topic in the field of urban transportation. Current research mainly uses several statistical indicators of complex networks to analyze the road network systems. However, these methods are essentially node-based. These node-based methods are more concerned with the number of connections between nodes, and lack of consideration for interactions. So, this leads to the well-known node paradox problem, and their ability of characterizing the local and intrinsic properties of a network is weak. From the perspective of network intrinsic geometry, this paper proposes a method for measuring road network vulnerability using a discrete Ricci curvature, which can identify the key sections of a road network and indicate its fragile elements. The results show that our method performs better than complex network statistics on measuring the vulnerability of a road network. Additionally, it can characterize the * Corresponding author evolution of the road network vulnerability among different periods of time in the same city through our method. Finally, we compare our method with the previous method of centrality and show the different between them. This article provides a new perspective on a geometry to analyze the vulnerability of a road network and describes the inherent nature of the vulnerability of a road system from a new perspective. It also contributes to enriching the analytical methods of complex road networks.

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“…A variety of methods have been developed to alleviate traffic congestion in different types of urban transportation networks (i.e. road networks, subway networks, and bus service networks) [3–10]. Given that road networks usually have the most complex network topologies and drivers have complicated route‐selection behaviours, traffic congestion problems have been mostly studied on road networks among different types of urban transportation networks.…”

Section: Introductionmentioning

confidence: 99%